{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T08:00:56Z","timestamp":1776931256756,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":127,"publisher":"ACM","funder":[{"name":"German Federal Ministry of Research, Technology and Space","award":["03SF0694A"],"award-info":[{"award-number":["03SF0694A"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,13]]},"DOI":"10.1145\/3772318.3790359","type":"proceedings-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T05:14:30Z","timestamp":1776057270000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Mental Workload Prediction Using Physiological Signals: Balancing Performance and Interpretability"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3953-6366","authenticated-orcid":false,"given":"Stephanie","family":"Hochgeschurz","sequence":"first","affiliation":[{"name":"Fraunhofer FKIE, Wachtberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3942-4057","authenticated-orcid":false,"given":"Jessica","family":"Schwarz","sequence":"additional","affiliation":[{"name":"Fraunhofer FKIE, Wachtberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9937-0762","authenticated-orcid":false,"given":"Thomas","family":"Ernst Ferdinand Witte","sequence":"additional","affiliation":[{"name":"Fraunhofer FKIE, Wachtberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,4,13]]},"reference":[{"key":"e_1_3_3_1_1_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.812677"},{"key":"e_1_3_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.549524"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3349495"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s40860-024-00240-0"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.carj.2019.06.002"},{"key":"e_1_3_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1469-8986.1993.tb01731.x"},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.21105\/joss.02621"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1111\/anae.12455"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2021.104510"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.3390\/s22197300"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.3389\/fnhum.2016.00647"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.3758\/s13428-020-01364-w"},{"key":"e_1_3_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apergo.2018.08.028"},{"key":"e_1_3_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.janxdis.2024.102960"},{"key":"e_1_3_3_1_16_2","volume-title":"Deep learning with Python","author":"Chollet Francois","unstructured":"Francois Chollet. 2021. Deep learning with Python: Second Edition. Manning Publications Co., New York, NY."},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.4324\/9780203771587"},{"key":"e_1_3_3_1_18_2","volume-title":"Arnegard","author":"Comstock James R.","year":"1992","unstructured":"James R. Comstock and Ruth J. Arnegard. 1992. The multi-attribute task battery for human operator workload and strategic behavior research. NASA Technical Memorandum No. 104174. NASA Langley Research Center, Hampton, VA."},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1002\/smi.3496"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3523491"},{"key":"e_1_3_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2022.3186625"},{"key":"e_1_3_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.3238\/arztebl.2009.0335"},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/3561048"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0294069"},{"key":"e_1_3_3_1_25_2","first-page":"3","article-title":"Ultra-short-term heart rate variability indexes at rest and post-exercise in athletes: Evaluating the agreement with accepted recommendations","volume":"13","author":"Esco Michael R.","year":"2014","unstructured":"Michael R. Esco and Andrew A. Flatt. 2014. Ultra-short-term heart rate variability indexes at rest and post-exercise in athletes: Evaluating the agreement with accepted recommendations. J. Sports Sci. Med. 13, 3 (September 2014), 535\u2013541.","journal-title":"J. Sports Sci. Med."},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpsycho.2004.11.003"},{"key":"e_1_3_3_1_27_2","unstructured":"Felipe Farias Teresa Ludermir and Carmelo Bastos-Filho. 2020. Similarity based stratified splitting: an approach to train better classifiers. arXiv:2010.06099v1. Retrieved from http:\/\/\u200barxiv.org\u200b\/\u200bpdf\/\u200b2010.06099."},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.3758\/BRM.41.4.1149"},{"key":"e_1_3_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.3758\/BF03193146"},{"key":"e_1_3_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3521649"},{"key":"e_1_3_3_1_31_2","volume-title":"Discovering statistics using R","author":"Field Andy","unstructured":"Andy Field, Jeremy Miles, and Zo\u00eb Field. 2012. Discovering statistics using R. Sage, London."},{"key":"e_1_3_3_1_32_2","volume-title":"Maschinelles Lernen: Grundlagen und Algorithmen in Python [Machine Learning: Fundamentals and algorithms in Python]","author":"Frochte J\u00f6rg","year":"2021","unstructured":"J\u00f6rg Frochte. 2021. Maschinelles Lernen: Grundlagen und Algorithmen in Python [Machine Learning: Fundamentals and algorithms in Python]. (3rd ed.). Hanser eLibrary. Carl Hanser Verlag M\u00fcnchen, M\u00fcnchen.","edition":"3"},{"key":"e_1_3_3_1_33_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-58625-0_7"},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1080\/00140139308967972"},{"key":"e_1_3_3_1_35_2","volume-title":"Python feature engineering cookbook: Over 70 recipes for creating, engineering, and transforming features to build machine learning models","author":"Galli Soledad","unstructured":"Soledad Galli. 2022. Python feature engineering cookbook: Over 70 recipes for creating, engineering, and transforming features to build machine learning models. (2nd ed.). Packt Publishing, Birmingham.","edition":"2"},{"key":"e_1_3_3_1_36_2","doi-asserted-by":"publisher","DOI":"10.1044\/2023_JSLHR-23-00273"},{"key":"e_1_3_3_1_37_2","volume-title":"Deep learning. Adaptive Computation and Machine Learning","author":"Goodfellow Ian","unstructured":"Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016. Deep learning. Adaptive Computation and Machine Learning. The MIT Press, Cambridge, MA."},{"key":"e_1_3_3_1_38_2","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/8146809"},{"key":"e_1_3_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-polisci-053119-015921"},{"key":"e_1_3_3_1_40_2","unstructured":"Mark A. Hall. 1999. Correlation-based feature selection for machine learning. PhD Thesis Department of Computer Science University of Waikato."},{"key":"e_1_3_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1007\/11538059_91"},{"key":"e_1_3_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.117787"},{"key":"e_1_3_3_1_43_2","doi-asserted-by":"publisher","DOI":"10.1177\/154193120605000909"},{"key":"e_1_3_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2008.4633969"},{"key":"e_1_3_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-61562-6"},{"key":"e_1_3_3_1_46_2","doi-asserted-by":"publisher","DOI":"10.3390\/s18051339"},{"key":"e_1_3_3_1_47_2","doi-asserted-by":"publisher","DOI":"10.1177\/0002716215570279"},{"key":"e_1_3_3_1_48_2","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2014.00322"},{"key":"e_1_3_3_1_49_2","volume-title":"Retrieved","author":"Hsu Chih-Wei","year":"2003","unstructured":"Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin. 2003. A practical guide to support vector classification. Retrieved August 29, 2025 from https:\/\/\u200bwww.csie.ntu.edu.tw\u200b\/\u223c\u200bcjlin\/\u200bpapers\/\u200bguide\/\u200bguide.pdf."},{"key":"e_1_3_3_1_50_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3082423"},{"key":"e_1_3_3_1_51_2","doi-asserted-by":"publisher","DOI":"10.25077\/josi.v22.n2.p81-98.2023"},{"key":"e_1_3_3_1_52_2","first-page":"3","article-title":"Bioharness\u2122 multivariable monitoring device","volume":"11","author":"Johnstone James A.","year":"2012","unstructured":"James A. Johnstone, Paul A. Ford, Gerwyn Hughes, Tim Watson, and Andrew T. Garrett. 2012. Bioharness\u2122 multivariable monitoring device. Part. I: Validity. J. Sports Sci. Med. 11, 3 (September 2012), 400\u2013408.","journal-title":"Part. I: Validity. J. Sports Sci. Med."},{"key":"e_1_3_3_1_53_2","doi-asserted-by":"publisher","DOI":"10.1002\/cphy.c130051"},{"key":"e_1_3_3_1_54_2","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6579\/aad7e6"},{"key":"e_1_3_3_1_55_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2024.3460750"},{"key":"e_1_3_3_1_56_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10654-011-9563-8"},{"key":"e_1_3_3_1_57_2","first-page":"111","article-title":"Data preprocessing for supervised leaning","volume":"1","author":"Kotsiantis Sotiris B.","year":"2006","unstructured":"Sotiris B. Kotsiantis, Dimitris Kanellopoulos, and Panagiotis E. Pintelas. 2006. Data preprocessing for supervised leaning. IJCS 1, 1, 111\u2013116.","journal-title":"IJCS"},{"key":"e_1_3_3_1_58_2","unstructured":"Alexandre Lacoste Alexandra Luccioni Victor Schmidt and Thomas Dandres. 2019. Quantifying the carbon emissions of machine learning. arXiv:1910.09700v2. Retrieved from http:\/\/\u200barxiv.org\u200b\/\u200bpdf\/\u200b1910.09700."},{"key":"e_1_3_3_1_59_2","doi-asserted-by":"publisher","DOI":"10.1002\/hfm.20269"},{"key":"e_1_3_3_1_60_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsycho.2011.11.009"},{"key":"e_1_3_3_1_61_2","doi-asserted-by":"publisher","DOI":"10.1631\/FITEE.1601516"},{"key":"e_1_3_3_1_62_2","unstructured":"Yuan-Cheng Liu Nikol Figalov\u00e1 J\u00fcrgen Pichen Philipp Hock Martin Baumann and Klaus Bengler. 2023. Workload assessment of human-machine interface: A simulator study with psychophysiological measures. arXiv:2406.09603v1. Retrieved from http:\/\/\u200barxiv.org\u200b\/\u200bpdf\/\u200b2406.09603v1."},{"key":"e_1_3_3_1_63_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.883321"},{"key":"e_1_3_3_1_64_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.biopsycho.2015.11.013"},{"key":"e_1_3_3_1_65_2","doi-asserted-by":"publisher","DOI":"10.3758\/s13428-020-01516-y"},{"key":"e_1_3_3_1_66_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.promfg.2015.07.783"},{"key":"e_1_3_3_1_67_2","doi-asserted-by":"publisher","DOI":"10.1080\/1463922X.2018.1547459"},{"key":"e_1_3_3_1_68_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10484-019-09445-z"},{"key":"e_1_3_3_1_69_2","doi-asserted-by":"publisher","DOI":"10.3389\/fcomp.2021.775282"},{"key":"e_1_3_3_1_70_2","doi-asserted-by":"publisher","DOI":"10.1093\/jcr\/ucx110"},{"key":"e_1_3_3_1_71_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2018.07.007"},{"key":"e_1_3_3_1_72_2","unstructured":"Christoph Molnar. 2019. Interpretable machine learning: A guide for making black box models explainable. Leanpub British Columbia."},{"key":"e_1_3_3_1_73_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-19-6755-9_24"},{"key":"e_1_3_3_1_74_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpsycho.2011.10.011"},{"key":"e_1_3_3_1_75_2","volume-title":"Python Data Analysis: Perform data collection, data processing, wrangling, visualization, and model building using Python","author":"Navlani Avinash","unstructured":"Avinash Navlani, Armando Fandango, and Ivan Idris. 2021. Python Data Analysis: Perform data collection, data processing, wrangling, visualization, and model building using Python. (3rd ed.). Packt Publishing, Birmingham.","edition":"3"},{"key":"e_1_3_3_1_76_2","doi-asserted-by":"publisher","DOI":"10.3233\/OER-2007-7202"},{"key":"e_1_3_3_1_77_2","doi-asserted-by":"publisher","DOI":"10.1109\/HIBIT.2010.5478895"},{"key":"e_1_3_3_1_78_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-42393-7"},{"key":"e_1_3_3_1_79_2","doi-asserted-by":"publisher","DOI":"10.1207\/S15326985EP3801_8"},{"key":"e_1_3_3_1_80_2","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.n71"},{"key":"e_1_3_3_1_81_2","doi-asserted-by":"publisher","DOI":"10.1145\/1743666.1743701"},{"key":"e_1_3_3_1_82_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2014.01344"},{"key":"e_1_3_3_1_83_2","first-page":"85","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa Fabian","year":"2011","unstructured":"Fabian Pedregosa, Ga\u00ebl Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, and \u00c9douard Duchesnay. 2011. Scikit-learn: Machine learning in Python. J. Mach. Learn. Res. 12, 85 (October 2011), 2825\u20132830.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_3_1_84_2","doi-asserted-by":"publisher","DOI":"10.3390\/brainsci14020149"},{"key":"e_1_3_3_1_85_2","first-page":"12","article-title":"Python Language Reference","volume":"3","author":"Foundation Python Software","year":"2023","unstructured":"Python Software Foundation. 2023. Python Language Reference, Version 3.12. Python Software Foundation, Wilmington, DE.","journal-title":"Version"},{"key":"e_1_3_3_1_86_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.imu.2021.100575"},{"key":"e_1_3_3_1_87_2","doi-asserted-by":"publisher","DOI":"10.3389\/fdata.2020.00018"},{"key":"e_1_3_3_1_88_2","doi-asserted-by":"publisher","DOI":"10.3390\/biomedinformatics4010048"},{"key":"e_1_3_3_1_89_2","doi-asserted-by":"publisher","DOI":"10.1145\/3491102.3501967"},{"key":"e_1_3_3_1_90_2","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering9110711"},{"key":"e_1_3_3_1_91_2","doi-asserted-by":"publisher","DOI":"10.1080\/00140130802120267"},{"key":"e_1_3_3_1_92_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0087357"},{"key":"e_1_3_3_1_93_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2021.683388"},{"key":"e_1_3_3_1_94_2","unstructured":"Cynthia Rudin. 2019. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. arXiv:1811.10154v3. Retrieved from http:\/\/\u200barxiv.org\u200b\/\u200bpdf\/\u200b1811.10154."},{"key":"e_1_3_3_1_95_2","volume-title":"Artificial intelligence: A modern approach","author":"Russell Stuart","unstructured":"Stuart Russell and Peter Norvig. 2021. Artificial intelligence: A modern approach. (4th ed.). Pearson, M\u00fcnchen.","edition":"4"},{"key":"e_1_3_3_1_96_2","doi-asserted-by":"publisher","DOI":"10.1017\/aer.2024.122"},{"key":"e_1_3_3_1_97_2","volume-title":"The Multi-Attribute Task Battery II (MATB-II) software for human performance and workload research: A user's guide. NASA\/TM-2011-217164","author":"Santiago-Espada Yamira","unstructured":"Yamira Santiago-Espada, Robert R. Myer, Kara A. Latorella, and Comstock, James R., Jr. 2011. The Multi-Attribute Task Battery II (MATB-II) software for human performance and workload research: A user's guide. NASA\/TM-2011-217164. NASA Langley Research Center, Hampton, VA."},{"key":"e_1_3_3_1_98_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2019.00813"},{"key":"e_1_3_3_1_99_2","doi-asserted-by":"publisher","DOI":"10.1111\/tops.12669"},{"key":"e_1_3_3_1_100_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2016.00050"},{"key":"e_1_3_3_1_101_2","volume-title":"Retrieved","author":"Schwabe Carlos","year":"2021","unstructured":"Carlos Schwabe. 2021. Scikit-Learn pipeline transformers - The hassle of transforming target variables (Part 1). Retrieved April 10, 2025 from https:\/\/\u200bmedium.com\u200b\/\u200banalytics-vidhya\/\u200bscikit-learn-pipeline-transformers-the-hassle-of-transforming-target-variables-part-1-6dfb714e2aad."},{"key":"e_1_3_3_1_102_2","doi-asserted-by":"publisher","DOI":"10.1201\/9781003215349-3"},{"key":"e_1_3_3_1_103_2","doi-asserted-by":"publisher","DOI":"10.1177\/00187208241285513"},{"key":"e_1_3_3_1_104_2","doi-asserted-by":"publisher","DOI":"10.4103\/ijoy.IJOY_27_17"},{"key":"e_1_3_3_1_105_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpsycho.2014.01.010"},{"key":"e_1_3_3_1_106_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-93715-7_23"},{"key":"e_1_3_3_1_107_2","first-page":"3","article-title":"Explaining odds ratios","volume":"19","author":"Szumilas Magdalena","year":"2010","unstructured":"Magdalena Szumilas. 2010. Explaining odds ratios. J. Can. Acad. Child Adolesc. Psychiatry 19, 3 (August 2010), 227\u2013229.","journal-title":"J. Can. Acad. Child Adolesc. Psychiatry"},{"key":"e_1_3_3_1_108_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph16152716"},{"key":"e_1_3_3_1_109_2","doi-asserted-by":"publisher","DOI":"10.1080\/00140139608964495"},{"key":"e_1_3_3_1_110_2","doi-asserted-by":"publisher","DOI":"10.1155\/ahci\/9313239"},{"key":"e_1_3_3_1_111_2","volume-title":"Tobii Pro Fusion","unstructured":"Tobii. 2019. Tobii Pro Fusion, Stockholm, Sweden. https:\/\/www.tobii.com\/"},{"key":"e_1_3_3_1_112_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0224365"},{"key":"e_1_3_3_1_113_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2023.105026"},{"key":"e_1_3_3_1_114_2","doi-asserted-by":"publisher","DOI":"10.3390\/s24123723"},{"key":"e_1_3_3_1_115_2","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2015.2476818"},{"key":"e_1_3_3_1_116_2","doi-asserted-by":"publisher","DOI":"10.1080\/14639220210123806"},{"key":"e_1_3_3_1_117_2","doi-asserted-by":"publisher","DOI":"10.1518\/001872008X288394"},{"key":"e_1_3_3_1_118_2","doi-asserted-by":"publisher","DOI":"10.1177\/154193121005400317"},{"key":"e_1_3_3_1_119_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-48060-7_26"},{"key":"e_1_3_3_1_120_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apergo.2024.104305"},{"key":"e_1_3_3_1_121_2","doi-asserted-by":"publisher","DOI":"10.1007\/s41664-018-0068-2"},{"key":"e_1_3_3_1_122_2","doi-asserted-by":"publisher","DOI":"10.1080\/00140139.2014.956151"},{"key":"e_1_3_3_1_123_2","doi-asserted-by":"crossref","unstructured":"Mark S. Young and N. A. Stanton. 2005. Mental workload. In Handbook of Human Factors and Ergonomics Methods N. A. Stanton A. Hedge Karel A. Brookhuis Eduardo Salas and H. W. Hendrick Eds. CRC Press London 39-1\u201339-9.","DOI":"10.1201\/9780203489925.ch39"},{"key":"e_1_3_3_1_124_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2021.08.007"},{"key":"e_1_3_3_1_125_2","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2017.00129"},{"key":"e_1_3_3_1_126_2","volume-title":"Feature engineering for machine learning: Principles and techniques for data scientists","author":"Zheng Alice","unstructured":"Alice Zheng and Amanda Casari. 2018. Feature engineering for machine learning: Principles and techniques for data scientists. O'Reilly Media, Inc., Sebastopol, CA."},{"key":"e_1_3_3_1_127_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-33342-2"}],"event":{"name":"CHI 2026: CHI Conference on Human Factors in Computing Systems","location":"Barcelona Spain","acronym":"CHI '26","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3772318.3790359","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T09:08:01Z","timestamp":1776416881000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3772318.3790359"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,13]]},"references-count":127,"alternative-id":["10.1145\/3772318.3790359","10.1145\/3772318"],"URL":"https:\/\/doi.org\/10.1145\/3772318.3790359","relation":{},"subject":[],"published":{"date-parts":[[2026,4,13]]},"assertion":[{"value":"2026-04-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}